Minimizing inter-symbol interference in ofdm signals

ABSTRACT

Methods and OFDM receivers for decoding an OFDM signal include estimating a channel impulse response from a pilot-dense symbol of the OFDM signal for each of a plurality of potential FFT window positions; determining a noise floor of each of the channel impulse responses; selecting the potential window position corresponding to the channel impulse response with the lowest noise floor as an optimum FFT window position; and decoding symbols of the OFDM signal using the optimum FFT window position.

BACKGROUND

Orthogonal frequency-division multiplexing (OFDM) is a specialmulti-carrier modulation (MCM) technique in which a single data streamis transmitted over a number of lower rate orthogonal sub-carriers. AnOFDM signal is generated from a serial stream of binary digits bydividing the input stream into N parallel streams. Each stream is mappedto a symbol stream using a modulation scheme, such as QAM (QuadratureAmplitude Modulation) or PSK (Phase-Shift Keying). An inverse fastFourier transform (IFFT) is computed on each set of symbols to transforma set of sub-carriers into a time-domain signal. Each set of symbolstransmitted at the same time is referred to as an OFDM symbol.

FIG. 1 illustrates an example OFDM frame 102 which comprises a block ofOFDM symbols 104. To eliminate or reduce inter-symbol interference (ISI)a guard interval (GI) 106 is appended at the start of the data portion108 of each symbol 104. As long as echoes fall within this interval,they will not affect the receiver's ability to correctly decode thesymbol. Generally a cyclic prefix consisting of the end portion 110 ofthe data portion 108 of the symbol is transmitted during the guardinterval 106.

Each OFDM symbol is decoded at an OFDM receiver by performing a FFT(Fast Fourier Transform) on the data portion 108 of the symbol 104.However, since the guard interval 106 includes a duplicate of the endportion 110 of the data portion 108 the FFT can be performed on anyportion of the symbol equal to the data length. This is because anyportion of the symbol equal to the data length will comprise all of thedata. The portion of the symbol on which the FFT is performed isreferred to as the FFT window. This may also alternatively be referredto as the FFT symbol window.

Accordingly, as shown in FIG. 2, the start of the FFT window for aparticular symbol 104 may be positioned anywhere between the start 202and end 204 of the guard interval 106. In particular, the FFT window maybe at position A 206, position B 208 or anywhere in between (e.g.position C 210). The start 202 of the guard interval 106 may also bereferred to as the starting edge, leading edge or the first edge of theguard interval 106. Similarly the end 204 of the guard interval 106 mayalso be referred to as the ending edge, following edge or the secondedge of the guard interval 106.

In wireless OFDM systems an OFDM signal generated by a transmitter willtypically reach the receiver via many different paths. For example, asshown in FIG. 3, the OFDM receiver may receive a primary or main signal302 comprising symbol A; and a secondary signal or echo 304 alsocomprising symbol A, which is positively or negatively delayed in timewith respect to the strongest main signal 302. It is advantageous toposition the FFT window so the most amount of energy can be obtainedfrom both the main signal 302 and the echo 304. For example, in FIG. 3,ideally the FFT window is positioned in the period 306 during which themain signal 302 and the echo 304 overlap (i.e. from the start of themain signal 302 until the end of the echo signal 304) so that symbol Acan be correctly decoded via the main signal 302 and the echo 304.Accordingly, in the example of FIG. 3, the FFT window is preferablypositioned at position A 308, position B 310 or anywhere in between(e.g. position C 312).

It is important to position the window correctly because distortions canarise by mis-positioning the FFT window. However, determining thecorrect location for the FFT window is difficult since there aretypically many echoes or secondary signals, some of which may be quiteweak (e.g. below 20 dB).

The embodiments described below are not limited to implementations whichsolve any or all of the disadvantages of known OFDM receivers.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

Described herein are methods and OFDM receivers for decoding an OFDMsignal. The method includes estimating a channel impulse response from apilot-dense symbol of the OFDM signal for each of a plurality ofpotential FFT window positions; determining a noise floor of each of thechannel impulse responses; selecting the potential window positioncorresponding to the channel impulse response with the lowest noisefloor as an optimum FFT window position; and decoding symbols of theOFDM signal using the optimum FFT window position.

A first aspect provides a method of decoding an OFDM signal at an OFDMreceiver, the method comprising: estimating a channel impulse responsefrom a received pilot-dense symbol of the OFDM signal for each of aplurality of potential FFT window positions; determining a noise floorof each of the channel impulse responses; selecting the potential FFTwindow position corresponding to the channel impulse response with thelowest noise floor as an optimum FFT window position; and decodingsymbols of the OFDM signal using the optimum FFT window position.

A second aspect provides an OFDM receiver comprising a channel impulseresponse generation module configured to estimate a channel impulseresponse from a pilot-dense symbol of an OFDM signal for each of aplurality of potential FFT window positions; a noise floor estimationmodule configured to determine a noise floor of each of the estimatedchannel impulse responses; and a FFT window position selection moduleconfigured to select the potential window position corresponding to theestimated channel impulse response with a lowest noise floor as anoptimum FFT window position.

The methods described herein may be performed by a computer configuredwith software in machine readable form stored on a non-transitorystorage medium, e.g. in the form of a computer program comprisingcomputer readable program code for configuring a computer to perform theconstituent portions of described methods or in the form of a computerprogram comprising computer program code adapted to perform all thesteps of any of the methods described herein when the program is run ona computer and where the computer program may be embodied on a computerreadable storage medium. Examples of such storage media include disks,thumb drives, memory cards etc. and do not include transitory signals.The software can be suitable for execution on a parallel processor or aserial processor such that the method steps may be carried out in anysuitable order, or simultaneously.

The hardware components described herein may be generated by anon-transitory computer readable storage medium having encoded thereoncomputer readable program code.

This acknowledges that firmware and software can be separately used andvaluable. It is intended to encompass software, which runs on orcontrols “dumb” or standard hardware, to carry out the desiredfunctions. It is also intended to encompass software which “describes”or defines the configuration of hardware, such as HDL (hardwaredescription language) software, as is used for designing silicon chips,or for configuring universal programmable chips, to carry out desiredfunctions.

The preferred features may be combined as appropriate, as would beapparent to a skilled person, and may be combined with any of theaspects of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention will be described, by way of example, withreference to the following drawings, in which:

FIG. 1 is a schematic diagram of an OFDM frame;

FIG. 2 is a schematic diagram of possible FFT window positions fordecoding an OFDM symbol;

FIG. 3 is a schematic diagram of possible FFT window positions fordecoding a multipath OFDM symbol;

FIG. 4 is a schematic diagram of a DVB-T2 frame;

FIG. 5 is a flow chart of an example method for selecting an FFT windowposition for decoding symbols in an OFDM signal;

FIG. 6 is a schematic diagram illustrating a method for selectingpotential FFT window positions for decoding a pilot-dense symbol;

FIG. 7 is a flow chart of an example method of generating a channelimpulse response for a specific FFT window position for a pilot-densesymbol;

FIG. 8 is a schematic diagram illustrating an example method ofextracting active sub-carriers from a frequency domain representation ofa pilot-dense symbol;

FIG. 9 is a schematic diagram illustrating an example method ofperforming slope cancellation on a frequency domain representation of apilot-dense symbol;

FIG. 10 is a schematic diagram illustrating an example method ofextracting pilot sub-carriers from a frequency domain representation ofa pilot-dense symbol;

FIG. 11 is schematic diagram of an example method of selecting potentialFFT window positions that are centered around the guard interval edges;

FIG. 12 is flow chart of an example method of determining the noiselevel of a channel impulse response;

FIG. 13 is a block diagram of an example OFDM receiver for implementingthe method of FIG. 5;

FIG. 14 is a schematic diagram illustrating channel impulse responsepath position ambiguity;

FIG. 15 is a schematic diagram illustrating a number of time-shifted orrotated channel impulse responses;

FIG. 16 is a flow chart of an example method for identifying the centerof a channel impulse response; and

FIG. 17 is a schematic diagram illustrating graphs of the calculated CIRnoise floors as a function of FFT window position for two example mainsignal and echo combinations.

Common reference numerals are used throughout the figures to indicatesimilar features.

DETAILED DESCRIPTION

Embodiments of the present invention are described below by way ofexample only. These examples represent the best ways of putting theinvention into practice that are currently known to the Applicantalthough they are not the only ways in which this could be achieved. Thedescription sets forth the functions of the example and the sequence ofsteps for constructing and operating the example. However, the same orequivalent functions and sequences may be accomplished by differentexamples.

As described above, selecting the position of the FFT window to use indecoding symbols of an OFDM signal is an important task as distortionscan arise from mis-positioning the FFT window. In particular, thedistortions arising from mis-positioning the FFT window typicallycomprise inter-symbol interference (ISI) (i.e. adjacent symbolinterference) and inter-carrier interference (ICI) (i.e. adjacent orself sub-carrier interference) which is commonly referred to as thetotal ISI.

Many known techniques to identify and select an FFT window make use ofthe pilot information embedded within an OFDM signal. In particular,each OFDM symbol is formed by data mapped onto a plurality ofsub-carrier frequencies or cells. However, not all of the cells (orsub-carriers) are used to transmit data. Various cells, referred to aspilot cells, within an OFDM frame are modulated with referenceinformation that is known to the receiver. These cells are thentransmitted at a “boosted” power level. The pilots can be used for framesynchronization, frequency synchronization, time synchronization,channel estimation, transmission mode etc.

Existing solutions for identifying the FFT window position can beclassified as either pilot-based or non-pilot based. For example, onepilot-based method relies on early-late power measurement of the pilots.Another non-pilot based method employs guard period correlation. Suchmethods generally tend to: lack sensitivity to weak echoes (e.g. below20 dB) resulting in a suboptimal FFT window position; lack sensitivityto wide echoes (e.g. 5 times the cyclic prefix) resulting in asuboptimal FFT window position; produce asymmetric performance dependingon whether echoes precede or proceed the main signal; have difficultiesdealing with complex channels with many multipath components of variousstrength; and/or produce carrier-to-noise (C/N) dependent performance,resulting in deterioration beyond a certain signal quality, or acombination thereof.

Described herein is a frequency-based, pilot-aided method for reliablyselecting the FFT window position so as to minimize total ISIparticularly in systems with heavy attenuation and wide echoes. Themethod includes, estimating a channel impulse response from apilot-dense symbol of an OFDM signal for each of a plurality ofestimated FFT window positions; determining a noise floor of each of thechannel impulse responses; and selecting the estimated window positioncorresponding to the channel impulse response with the lowest noisefloor as an optimum FFT window position.

In particular, some OFDM-based standards, such as DVB-T2 (Digital VideoBroadcasting-Second Generation Terrestrial), DVB-C2 (Digital VideoBroadcasting-Cable), and Advanced Television Systems Committee (ATSC)3.0 (as proposed) standards use pilot-dense symbols that have a highernumber (or higher density) of pilot cells than other symbols, such asdata symbols.

For example, reference is now made to FIG. 4 which illustrates theformat of a DVB-T2 frame 402. The DVB-T2 frame 402 comprises a P1 symbol404, one or more P2 symbols 406, and a number of normal or data symbols408 ₀ to 408 _(N) where N is an integer greater than 1. In someconfigurations the last data symbol may be a frame closing symbol (notshown). The P1 symbol is used for synchronization and signalingpurposes; the P2 symbol conveys L1 (layer 1) parameter configurationsand some PLP (physical layer pipe) data; and the data symbols carry PLPdata. In particular the P1 and P2 symbols carry L1 signalinginformation. The L1 signaling information is split into three mainsections: the P1 signaling 410 (which is carried in the P1 symbol),L1-pre signaling 412 and L1-post signaling 414 (both carried in the P2symbol). The L1 pre-signaling 412 enables the reception and decoding ofthe L1-post signaling 414, which in turn conveys the parameters neededby the receiver to access the physical layer pipes. The sub-carrierswhich are used to carry the L1-pre signaling information will bereferred to herein as the L1-pre sub-carriers; and the sub-carrierswhich are used to carry the L1-post signaling information will bereferred to herein as the L1-post sub-carriers.

All of the symbols, except the P1 symbol, (i.e. the P2 symbols, datasymbols and frame closing symbol) comprise pilot cells. In particular,the P2 symbol comprises P2 pilots; the normal or data symbols comprisescattered, continual, and edge pilots; and any frame closing symbolcomprises edge and frame-closing pilots. However, the P2 symbolcomprises a higher number of pilots than the data symbols and frameclosing symbols. As a result, a P2 symbol is considered to be apilot-dense symbol.

The number, position and amplitude of the pilot cells in a P2 symbol aredetermined by the DVB-T2 mode. For example, in 32K SISO (Single InputSingle Output) mode, every 6^(th) cell is a P2 pilot and theamplification is

$\frac{\sqrt{37}}{5};$

and in all other modes (including 32K MISO (Multiple Input SingleOutput)) every 3^(rd) cell is a P2 pilot and the amplification is

$\frac{\sqrt{31}}{5}.$

The higher number of pilots in a pilot-dense symbol, such as the P2symbol, allows an estimate of the channel impulse response (CIR) to bemade directly and solely from the pilots in the pilot-dense symbol. Inparticular, to sample a channel the frequency-axis sampling resolutionhas to be fine enough to capture the channel delay spread withoutaliasing. Only pilot-dense symbols have enough pilots to allow a highenough sampling resolution of pilots within a single symbol. Inparticular, in 8 MHz 32 k SISO the P2 symbol supports a Nyquist samplingfor delay spreads up to

${\frac{T_{u}}{6} = {597\mspace{14mu} {\mu s}}},$

where T_(u) is determined by the bandwidth and FFT size.

It is theoretically possible to estimate a channel impulse response fromthe pilots in a single data symbol, but it will have limited timeresolution and will generally be noisy. To generate a useful channelimpulse response from the pilots in the data symbols would requiremultiple data symbols to obtain enough pilot samples. For example, insome DVB-T2 modes it would take sixteen data symbols to obtain enoughinformation to be able to estimate a useful channel impulse response.Accordingly, estimating the CIR from the pilots in a pilot-dense symbolallows the CIR to be estimated without reliance on the data symbols orelaborate decision-directed techniques based on data-bearingsub-carriers.

As noted above, the mis-positioning of the FFT window gives rise tototal ISI (ICI+ISI). This can be shown mathematically where the receivedsignal s(t, τ) is represented as shown in equation (1):

$\begin{matrix}{{\overset{\_}{s}\left( {t,\tau} \right)} = \left\{ \begin{matrix}{s\left( {t + \tau} \right)} & {{{if}\mspace{14mu} 0} \leq t \leq {T - \tau}} \\{e\left( {t - \left( {T - \tau} \right)} \right)} & {{{{if}\mspace{14mu} T} - \tau} \leq t \leq T}\end{matrix} \right.} & (1)\end{matrix}$

where τ is a positive FFT window position offset; T is the symbolduration; e(t) is the interference due to mis-positioning, translated byFFT positional shift and symbol duration; and s(t) is the wanted signal.

Performing a discrete Fourier transform (DFT) on the received signalresults in a plurality of frequency domain bins X_(k) that represent aparticular sub-carrier or cell k as shown in equation (2). Manipulationof equation (2) illustrates that the frequency domain bin or cell can berepresented as the desired cell signal, plus ICI and ISI (referred to astotal ISI).

$\begin{matrix}{\mspace{20mu} {X_{k} = {\frac{1}{T}{\int_{0}^{t}{{\overset{\_}{s}\left( {t,\tau} \right)}e^{{- j}\; 2\pi \; f_{k}t}{dt}}}}}} & (2) \\{\mspace{20mu} {X_{k} = {{\frac{1}{T}{\int_{0}^{T - \tau}{{s\left( {t + \tau} \right)}e^{{- j}\; 2\pi \; f_{k}t}}}} + {\frac{1}{T}{\int_{T - \tau}^{T}{{e\left( {t - \left( {T - \tau} \right)} \right)}e^{{- j}\; 2\pi \; f_{k}t}{dt}}}}}}} & (3) \\{\mspace{20mu} {X_{k} = {{\frac{1}{T}{\int_{\tau}^{T}{{s(t)}e^{{- j}\; 2\pi \; {f_{k}{({t - \tau})}}}{dt}}}} + {\frac{1}{T}{\int_{T}^{T + \tau}{{e\left( {t - T} \right)}e^{{- j}\; 2\pi \; {f_{k}{({t - \tau})}}}{dt}}}}}}} & (4) \\{X_{k} = {{\frac{1}{T}{\int_{0}^{T}{{s(t)}e^{{- j}\; 2\pi \; {f_{k}{({t - \tau})}}}{dt}}}} - {\frac{1}{T}{\int_{0}^{\tau}{{s(t)}e^{{- j}\; 2\pi \; {f_{k}{({t - \tau})}}}{dt}}}} + {\frac{1}{T}{\int_{0}^{\tau}{{e(t)}e^{{- j}\; 2\pi \; {f_{k}{({t - \tau})}}}{dt}}}}}} & (5) \\{\mspace{20mu} {X_{k} = {{\frac{1}{T}{\int_{0}^{T}{{s(t)}e^{{- j}\; 2\pi \; {f_{k}{({t - \tau})}}}{dt}}}} - {{ICI}_{k}(\tau)} + {{ISI}_{k}(\tau)}}}} & (6)\end{matrix}$

The frequency bin or cell can be re-written as a function of the FFTwindow position as shown in equations (7) and (8) where S_(k) is thedesired sub-carrier signal.

$\begin{matrix}{{X_{k}(\tau)} = {{S_{k}e^{j\; 2\pi \; f_{k}\tau}} + {\frac{1}{T}{\int_{0}^{T}{\left\lbrack {{e(t)} - {s(t)}} \right\rbrack e^{{- j}\; 2\pi \; {f_{k}{({t - \tau})}}}{dt}}}}}} & (7) \\{{X_{k}(\tau)} = {{S_{k}e^{{j2}\; \pi \; f_{k}t}} + {{ICI}_{k}(\tau)} + {{ISI}_{k}(\tau)}}} & (8)\end{matrix}$

Since e^(j2ζf) ^(k) ^(τ) is a rotation term that can be cancelled at theOFDM receiver, provided that the guard interval is greater than thechannel extent, the term [e(t)−s(t)] can be nullified by the choice of τsuch that the total ISI is eliminated or reduced.

If S_(k) is a pilot of known amplitude and phase the channel impulseresponse (CIR) can be estimated. It is evident from equation (8) thatthe total ISI (ICI+ISI) will have a direct impact on the CIR, thus thetotal ISI (ICI+ISI) can be measured as a function of the windowposition, from the CIR, denoted CIR(τ).

Accordingly, if the CIR is determined for a plurality of different FFTwindow positions the noise floors of those CIRs indicate which of thoseFFT window positions has the least amount of total ISI.

Reference is now made to FIG. 5 which illustrates a method 500 ofselecting an FFT window for decoding symbols of a received OFDM signalby comparing channel impulse responses for various FFT window positionsfor a pilot-dense symbol (e.g. P2 symbol 406). The method 500 begins atblock 502 where a pilot-dense symbol (e.g. P2 symbol 406) is received.In some cases the received pilot-dense symbol may be stored in a buffer.Once the pilot-dense symbol is received (and optionally stored) themethod 500 proceeds to block 504.

At block 504 a plurality of possible or potential FFT window positionsfor decoding the received pilot-dense symbol are selected or identified.In one guard-agnostic formulation, the possible FFT window positions areselected by (i) estimating the start or first edge of the guardinterval, (ii) identifying a plurality of FFT window positions that areshifted left from the estimated start or first edge of the guardinterval; and (iii) identifying a plurality of FFT window positions thatare shifted right from the estimated start or first edge of the guardinterval.

For example, reference is now made to FIG. 6 which illustrates theselection of the possible or potential FFT window positions for decodinga received pilot-dense symbol 602. The start or first edge of the guardinterval 620 is estimated to occur at point 604 and the first potentialFFT window position is aligned with the estimated start or first edge ofthe guard interval. This first FFT window position may be referred to asthe locked or reference FFT window position 606. A plurality of FFTwindow positions shifted left from the locked or reference FFT windowposition 606 are then selected (e.g. left FFT window position A 608;left FFT window position B 610; and left FFT window position C 612); anda plurality of FFT window positions shifted right from the locked orreference FFT window position 606 are then selected (e.g. right FFTwindow position A 614; right FFT window position B 616; and right FFTwindow position C 618).

At the time the selection of possible or potential FFT window positionsis made, the OFDM receiver's confidence in its estimate of the guardinterval 620 is not very high. To mitigate against this uncertainty, theleft-right FFT window position selections may be anchored to a pointthat represents a best balance among all possible guard intervalconfigurations: narrowest to widest. Such an arrangement is referred toas a guard-agnostic selection formulation.

In certain wireless channels (e.g. terrestrial), a weak echo can eitherprecede or follow a much stronger main path. The echo can also be quitefar from the main path (e.g. 5 times outside the guard interval) forcertain configurations. It is, therefore, important that the FFT windowselection be extended to the left and right beyond a typical symbolperiod 622 as denoted by pre-symbol period 624 (e.g. left FFT windowpositions A, B and C 608, 610 and 612) and post-symbol period 626 (e.g.right FFT window position C 618), respectively. It is evident to aperson of skill in the art that the pre and/or post-symbol periods 624and 626 can be configured in any way or fashion by higher-level logic.

In some cases the FFT window positions are selected so as to be equallyspaced from each other. In other cases more FFT window positions areselected near the estimated or potential guard edges and fewer FFTwindow positions are selected farther from the estimated or potentialguard edges. Selecting the potential FFT window positions in this mannercan improve performance because, as described above, at the time thepotential FFT window positions are selected the OFDM receiver is notconfident that the transmitted guard interval 620 has been correctlyidentified. An example method of selecting a higher number of FFT windowpositions near the potential guard edges is described with reference toFIG. 11.

The number of potential FFT window positions that are selected may bebased on the amount of memory available and the OFDM frame length. Inparticular, it takes a certain amount of time to evaluate each possibleor potential FFT window position which is referred to herein as thenoise floor scan. Thus the higher the number of points (possible orpotential FFT window positions) used in the noise floor scan, the moretime it takes to reach a result. Equally, it is advantageous to reducethe number of frames that elapse before the noise floor scan yields aresult. This is because until a result is generated, the OFDM receivercannot yet transition to a full demodulation, which adds to the latencyof synchronization. Accordingly a balance has to be made between gettinga quick result and getting an accurate result. For ease of storage andcomputation the number of potential FFT window positions selected istypically a multiple of two. In some examples, one hundred andninety-two (192) FFT window positions are selected. However, it will beevident to a person of skill in the art that another number of FFTwindow positions may be used.

Once a potential or possible FFT window position has been selected,information identifying the selected FFT window position may be storedin memory. In some cases one point is stored for each selected FFTwindow position. For example, in some cases, the start position of eachpotential FFT window may be stored. In other cases, a shift value (avalue representing the shift in time relative to the estimate guardstart) may be stored.

Referring back to FIG. 5, once the plurality of potential FFT windowpositions have been selected the method 500 proceeds to block 506.

At block 506, for each potential FFT window position selected in block504, an estimate of the channel impulse response (CIR) is determinedfrom the pilots in the received pilot-dense symbol falling within theFFT window position. As described above, the number of pilots in apilot-dense symbols allows an estimate of the CIR to be directlydetermined from the pilots. In some cases, estimating the channelimpulse response for a particular FFT window position comprisesperforming a FFT on the pilot-dense symbol samples falling within thewindow defined by the particular FFT window position to generate afrequency domain representation of the pilot-dense symbol, extractingthe pilots from the frequency domain representation of the pilot-densesymbol, and taking an IFFT of the extracted pilots to generate anestimate of the CIR. An example method for estimating the channelimpulse response for a particular FFT window position is described withreference to FIG. 7. Once an estimate of the CIR has been determined foreach of the possible FFT window positions, the method 500 proceeds toblock 508.

At block 508, the noise floor of each CIR generated in block 506 isestimated. As described above, comparing the change in CIR noise flooras the FFT window position is shifted allows the presence of total ISIto be inferred. In particular, if the noise floor at shift m is denotedn_(CLR), then n_(CLR) is equal to the additive noise, n₀, whichrepresents the lowest bound on noise after two DFT (discrete Fouriertransform) projections (forward and inverse), and the noise due to totalISI, n_(ISI), as shown in equation (9):

n _(CLR)(m)=n ₀ +n _(LSI)(m)  (9)

Given an appropriate channel coherence time under a worst case(slow-enough) fade regime, n₀ is assumed constant within the vicinity ofthe different window positions. An example method of determining thenoise floor of a CIR is described with reference to FIG. 12.

Once the noise floor for the estimated CIRs has been estimated themethod 500 proceeds to block 510.

At block 510 the FFT window position having the lowest CIR noise flooris selected as the optimum FFT window position for minimizing the totalISI. The optimum FFT window position may then be used to decode thesymbols in the OFDM signal.

Although the estimation of the CIRs and associated noise floors inblocks 506 and 508 are described above as being executed sequentiallyfor all of the potential FFT window positions (e.g. the CIR is estimatedfor each of the potential FFT window positions and then the noise flooris estimated for each of the estimated CIRs), in other examples the CIRsand associated noise floors may be determined in a different order. Forexample, in other cases the estimation of the CIR and correspondingnoise floor is done in parallel for each possible or potential FFTwindow position (e.g. the CIR and corresponding noise floor areestimated for possible or potential FFT window position A, and inparallel, the CIR and corresponding noise floor are estimated forpossible or potential FFT window position B). In yet other cases, theCIR and corresponding noise floor may be estimated for a particular FFTwindow position before the CIR and corresponding noise floor areestimated for the next FFT window position (e.g. the CIR andcorresponding noise floor are estimated for possible or potential FFTwindow position A; then the CIR and corresponding noise floor areestimated for possible or potential FFT window position B).

Reference is now made to FIG. 7 which illustrates an example method 700for estimating the channel impulse response (CIR) for a particular FFTwindow position from the pilots in a pilot-dense symbol. From an ISIperspective, the method 700 described herein leverages one forward andone inverse DFT kernels back-to-back to provide a distilled measure ofthe ISI-induced CIR noise floor which is easily separable. Consequently,ISI arising from very weak echoes (e.g. below 20 dB) can be robustlydetected. This is in contrast with other methods such as time-domain,correlation-based methods.

The method 700 begins at block 702 where a forward FFT is performed onthe samples that fall with the window defined by the particular FFTwindow position being evaluated. As is known to those of skill in theart an FFT converts a time domain representation of a signal into afrequency domain representation of the signal. Accordingly, the FFTreceives the samples of the pilot-dense symbol falling within the FFTwindow and generates a frequency domain representation of those samples.Once the FFT has been performed and the frequency domain representationhas been generated, the method 700 proceeds to block 704.

At block 704 the active sub-carriers are extracted from the frequencydomain representation generated at block 702. In particular, asdescribed above, in an OFDM system each cell of a symbol will betransmitted on a separate sub-carrier. However, not all of the possiblesub-carriers are used. A number of the sub-carriers are reserved for“nulls” and lower and higher frequency guard carriers. The sub-carriersthat are used to transmit data or information are referred to as theactive sub-carriers. The sub-carriers that are not used to transmit dataor information are referred to as the inactive sub-carriers.

Reference is now made to FIG. 8 which illustrates the distribution ofactive and inactive sub-carriers in the frequency domain. In particular,a FFT of size N will produce an FFT output (frequency domainrepresentation 802) comprising a first group of active sub-carriers 804separated from a second group of active sub-carriers 806 by a group ofinactive sub-carriers 808. Since the inactive sub-carriers 808 do notcarry any useful information they can be removed from the frequencydomain representation 802, leaving only the active sub-carriers. Thismodified frequency domain representation will be referred to herein asthe active sub-carrier frequency domain representation 810. Generatingthe active sub-carrier frequency domain representation 810 may comprisere-ordering the frequency domain representation 802 to make the activesub-carriers 806 and 804 a contiguous block 812 as shown in FIG. 8.

Referring back to FIG. 7, once the active sub-carriers have beenextracted from the frequency domain representation generated at block702, the method 700 proceeds to block 706.

At block 706, a slope cancellation is performed on the activesub-carrier frequency domain representation generated in block 704 tonullify the effect of the shift in time of the FFT window positionrelative to the locked or reference FFT window position. In particular,each possible FFT window position (other than the reference FFT windowposition itself) is time-shifted from the locked or reference FFT windowposition. If the time shift is not accounted for in the frequency domainthen the CIRs corresponding to the different possible FFT windowpositions will be time shifted with respect to each other making it moredifficult to accurately compare them.

Since a time shift corresponds to a change in the slope of the phase inthe frequency domain, a time shift is nullified or discounted in thefrequency domain by performing a phase slope cancellation. Accordingly,to nullify the time shift of the FFT window position a phase slopecancellation is performed on the active sub-carrier frequency domainrepresentation to generate a slope cancelled active sub-carrierfrequency domain representation. Performing the slope cancellationensures that the CIR for each possible FFT window position remains atthe same position in time regardless of the time shift in the FFT windowposition. This is important because, as described later with referenceto FIG. 12, if the CIR is time shifted, when the CIR is decimated toestimate the noise floor, CIR samples may fall into the wrong bin.

Reference is now made to FIG. 9 which illustrates an example method forperforming a phase slope cancellation for a particular FFT windowposition 902 which is shifted right from the estimated start or firstedge 910 of the guard interval 906 for the received pilot-dense symbol908. The amount of shift, T_(W), is equal to the difference in timebetween the estimated start or first edge 910 of the guard interval 906and the start or first edge 904 of the FFT window position 902.

In this example, the slope cancellation comprises performing anelement-wise multiplication 912 between the active sub-carrier frequencydomain representation 810 and a phase vector θ shown in equation (10)where θ₀ is the phase offset, θ_(t) is the phase increment and N_(U) isthe number of active sub-carriers:

θ=θ₀+[0, . . . ,N _(U)−1]×θ_(t)  (10)

The phase increment θ_(t) is equal to the shift T_(W) divided by thesize of the FFT, N, performed in block 702, as shown in equation (11):

$\begin{matrix}{\theta_{t} = {{\frac{T_{W}}{N} \cdot 2}\pi}} & (11)\end{matrix}$

The phase offset θ₀ is calculated in accordance with equation (12) whereΔ is calculated in accordance with equation (13).

$\begin{matrix}{\theta_{0} = \left( {\Delta \cdot \theta_{t}} \right)} & (12) \\{\Delta = {N - \frac{N_{U} - 1}{2}}} & (13)\end{matrix}$

Referring back to FIG. 7, once the phase slope cancellation has beenperformed, the method 700 proceeds to block 708.

At block 708, the PRBS (Pseudo-Random Binary Sequence) modulation iscancelled from the slope cancelled active sub-carrier frequency domainrepresentation generated at block 706. Some OFDM systems may modulatethe pilots according to a PRBS to avoid large peaks in the time-domainsignal. For example, in DVB-T2, the pilots are BPSK (binary phase shiftkeying) modulated according to a reference sequence derived from asymbol-level PRBS and a frame-level PN-sequence. These sequences areknown to the receiver and thus can be cancelled. The PRBS cancellationis performed on the slope cancelled active sub-carrier frequency domainrepresentation generated at block 706 to generate a PRBS and slopecancelled active sub-carrier frequency domain representation. In somecases the cancellation is an element-wise multiplication of the pilotsby the binary sequence to effectively demodulate their BPSK mapping.Once the PRBS modulation has been cancelled the method 700 proceeds toblock 710.

At block 710, the pilots are extracted from the PRBS and slope cancelledactive sub-carrier frequency domain representation generated at block708. At this stage, various cancellation steps leave the pilots affectedonly by the channel, facilitating a direct estimation of the CIR. Insome cases extracting the pilots may comprise locating the first pilotand then extracting each X^(th) sample of the PRBS and slope-cancelledactive sub-carrier frequency domain representation, where X is therepetition of the pilots in the pilot-dense symbol. For example, whereevery 6^(th) cell/sub-carrier is a pilot then every 6^(th) sample isextracted from the PRBS and slope cancelled frequency domainrepresentation.

Reference is now made to FIG. 10 which illustrates extraction of thepilot sub-carriers 1002 of a slope cancelled active sub-carrierfrequency domain representation 1004. As described above the pilotsub-carriers 1002 are boosted as compared to the non-pilot or regularsub-carriers 1006. In the example shown in FIG. 10 every 6^(th) activesub-carrier is a pilot sub-carrier 1002. Extracting the sub-pilotsresults in a pilot frequency domain representation 1008 that comprisesonly the pilot sub-carriers 1002.

Referring back to FIG. 7, once the pilot frequency domain representationhas been generated, the method 700 proceeds to block 712.

At block 712, the pilot frequency domain representation generated atblock 710 is scaled or amplified to be at a certain level to maximizethe dynamic range of the IFFT module used in block 716. In someexamples, the scale or amplification is determined from the locked orreference FFT window position and then the same scale is applied to thepilot frequency domain representation for each other possible orpotential FFT window position being evaluated. The scale oramplification may be selected by determining the normalized power of thepilot-dense symbol signal as defined by the locked or reference FFTwindow position and identifying a scale or amplification value to applyto the signal to place it at a certain level to maximize the dynamicrange of the IFFT module. This produces a more accurate CIR and thusallows the noise floor of the CIR to be more accurately measured. Oncethe pilot frequency domain representation has been scaled or amplifiedto generate a scaled pilot frequency domain representation, the method700 proceeds to block 714.

At block 714, the scaled pilot frequency domain representation generatedat block 712 is windowed to generate a windowed and scaled pilotfrequency domain representation. In other words a window function isapplied to the scaled pilot frequency domain representation. The windowfunction may serve a dual purpose. Firstly the window function mayselect a subset (e.g. a radix-2 subset) of all available pilots suchthat the IFFT can be taken directly. For example, where an IFFT of size5,000 is used, the window may be used to drop the number of samples toaround 4,096 which has shown to still produce a reliable result.

In some cases the window function is applied so that the samples closerto the center bandwidth (the center of the symbol) are selected or takenand the samples at the edges are not selected (e.g. windowed out). Thisis because the samples at the center are likely to be of better fidelity(e.g. free of adjacent channel interference).

Secondly, the window function may also apply a smoothing function inorder to combat the spectral leakage resulting from the finite pilotset. As such, the accuracy of the noise floor estimation may be furtherenhanced. Where sidelobe rejection is of importance, a classic Hammingwindow may be utilized for its excellent 40 dB sidelobe rejection andease of implementation on resource-constraint hardware. Once the scaledpilot frequency domain representation has been windowed, the method 700proceeds to block 716.

At block 716, an IFFT is taken of the windowed and scaled pilotfrequency domain representation generated at block 714 to generate a CIRfor the particular FFT window position being evaluated. As known tothose of skill in the art an IFFT converts a frequency domainrepresentation of a signal into a time domain representation of thesignal. As described above an accurate CIR can be obtained directly fromthe pilots in the pilot-dense symbol thus performing an IFFT of thewindowed and scaled pilot frequency domain representation produces anaccurate CIR for the particular FFT window position being evaluated.

As described above, an improvement in accuracy may be achieved byselecting and evaluating more FFT window positions near the estimatedguard interval edges and fewer FFT window positions farther away fromthe estimated guard interval edges. Reference is now made to FIG. 11which illustrates an example of how the potential FFT window positionscan be selected for maximal efficacy. In this example, the period 1100over which FFT window positions are selected is divided into fivedifferent phases 1102, 1104, 1106, 1108 and 1110. The phases 1102, 1104,1106, 1108 and 1110 vary in the density or ratio of FFT window positionselections (i.e. some phases have a higher density of selected windowposition than other phases). In this particular example, theconfiguration of the phases is designed to combat parameteruncertainties at acquire-time such as guard period or wide,outside-guard echoes.

In the example of FIG. 11, the OFDM signal is a DVB-T2 signal configuredfor an 8 MHz channel, 32 k and 1/128 guard interval. Accordingly, theguard interval is 28 μs or 256 baseband samples. In a narrow guardterrestrial broadcast, it is not uncommon to experience echoes whichspan significantly more than the guard duration. Superimposed on this isthe fact that the echo can precede or follow the much stronger mainpath. In addressing this, the second phase 1104, which is 5×28 μs=140μs, has a high density of FFT window position selections 1112. Thesecond phase 1104 is designed to select the correct FFT window positionwith fine resolution for an echo outside the guard interval up to 5times the guard interval.

Simultaneously, the OFDM receiver could have mis-estimated the 1/128guard at acquire-time when in fact the transmitted guard was 1/8=448 μs.Because of this uncertainty, the fourth phase 1108 returns back tohaving a high density of FFT window position selections after anintermediate third phase 1106 of medium-density FFT window positionselections such that the guard edge of a 448 μs guard is catered for.The first and fifth phases 1102 and 1110 have a low density of FFTwindow positions reflecting the unlikelihood of encountering significantechoes.

In FIG. 11, a total of one hundred ninety-two (192) potential FFT windowpositions are selected. This equates to 1239 μs at the 8 MHz example,which is a sizeable portion of the ˜3.6 ms 32 k mode symbol. Many otherdivisions of selected FFT window position configurations are possibleand the non-uniform FFT window position selection could be arbitrarilymade complex, defined programmatically, and adapted and configured byhigher-level applications.

Reference is now made to FIG. 12 which illustrates an example method1200 of estimating the noise level of a CIR for a particular FFT windowposition. The method 1200 begins at block 1202 where the CIR isdecimated into a number of bins to produce a decimated CIR. As is knownto those of skill in the art decimation is the process of dividing anumber of samples into groups (or bins) and then storing only one sampleor value to represent the group. In some cases the one value for eachgroup or bin may be the average of the values in that bin. The CIRtypically comprises thousands of samples and decimation reduces thenumber of samples significantly to a more amenable number for analysis.For example, in some cases, there may be 4,096 samples in the CIR whichare decimated to 128 samples (i.e. bins). The number of bins may beselected to achieve the best trade-off between resolution and analysiscomplexity. Once the CIR has been decimated the method 1200 proceeds toblock 1204.

At block 1204, a threshold is applied to the decimated CIR to eliminatethe bins or samples that are above the threshold. The threshold isselected to eliminate energy peaks that can be attributed to the symbolitself such that only the noise remains. In some cases, the threshold isselected to be a predetermined value (e.g. −12 dB) from the maximum binof the decimated CIR. However, it will be evident to a person of skillin the art that the threshold may be selected using other methods orprocedures. In some cases the threshold is selected only once. Forexample, the threshold may be selected based on the maximum bin of thedecimated CIR for the reference or locked FFT window position. Once thethreshold has been applied to the decimated CIR the method 1200 proceedsto block 1206.

At block 1206 the bins remaining after the threshold has been applied tothe decimated CIR are combined (e.g. summed or averaged) to produce arepresentation of the noise floor of the CIR. In general, the higher thecombination (e.g. sum or average), the more noise. Inherently, the moreof the power is attributed to the noise, the less power is attributed tothe symbol. Accordingly, more power will be attributed to the symbols(and thus ISI is reduced) by using the FFT window position with thelowest noise floor to decode the OFDM symbols.

Reference is now made to FIG. 13 which illustrates an example OFDMreceiver 1300 for selecting an FFT window position in accordance withthe methods described above. The OFDM receiver 1300 comprises four mainmodules—a potential FFT window position generation module 1302configured to generate the plurality of possible or potential FFT windowpositions based on one or more system configurations (e.g. FFT mode,guard interval (GI) etc.); a channel impulse response generation module1304 configured to generate a channel impulse response for each possibleor potential FFT window position generated by the potential FFT windowposition generation module 1302; a noise floor estimation module 1306configured to estimate the noise floor for each of the channel impulseresponses generated by the channel impulse response generation module1304; and an optimum FFT window position selection module 1308configured to select the potential FFT window position with the lowestnoise floor as the optimum FFT window position for minimizing total ISI.The optimum FFT window position can then be provided to a decode unit(not shown) for decoding the symbols of the OFDM signal.

In the example shown in FIG. 13, the potential FFT window positiongeneration module 1302 comprises a guard interval estimator 1310 and apossible FFT window position selection module 1312. The guard intervalestimator 1310 receives the received pilot-dense symbol 1314 andestimates the guard interval. The guard interval may be estimated usingany known techniques, such as, but not limited to, a correlation-basedsearch method. Once the guard interval has been estimated the possibleFFT window position selection module 1312 selects a number of FFT windowpositions that are shifted left and right from the start of theestimated guard interval as described above with reference to FIGS. 5, 6and 11. For example, as described above, the FFT window positions may beselected so they are equally spaced over the symbol period (including apre and post symbol interval) or they may be selected so that morepotential FFT window positions are selected near the estimated guardinterval edges and fewer potential FFT window positions are selectedfarther away from the estimated guard interval edges.

As described above, the channel impulse response generation module 1304is configured to generate or estimate a channel impulse response foreach possible or potential FFT window position generated by thepotential FFT window position generation module 1302. In general, foreach possible or potential FFT window position, the channel impulseresponse generation module 1304 takes the FFT of the receivedpilot-dense symbol 1314 samples that fall within the window defined bythe possible or potential FFT window position being evaluated togenerate a frequency domain representation of the pilot-dense symbol;extracts the pilot sub-carriers from the frequency domainrepresentation; and takes the IFFT of the extracted pilot sub-carrierfrequency domain representation to generate an estimate of the channelimpulse response for that possible or potential FFT window position.

In the example shown in FIG. 13, the channel impulse response generationmodule 1304 comprises an FFT module 1316, an active sub-carrierextraction module 1318, a slope cancellation module 1320, a pilotmodulation cancellation module 1322, a pilot extraction module 1324, ascale module 1326, a window module 1328, and an IFFT module 1330. TheFFT module 1316 receives information from the potential FFT windowposition generation module 1302 identifying the position of a particularFFT window, and the received pilot-dense symbol 1314, and takes the FFTof the samples of the received pilot-dense symbol 1314 that fall withinthe window at the identified position to generate a frequency domainrepresentation of the pilot-dense symbol. The active sub-carrierextraction module 1318 then extracts the active sub-carriers from thefrequency domain representation of the pilot-dense symbol using anysuitable means, such as, but not limited to, those described above withreference to FIGS. 7 and 8. For example, as described above, the activesub-carriers may be extracted by re-arranging the frequency domainrepresentation so that the active sub-carriers form a contiguous block.

The active sub-carrier frequency domain representation generated by theactive sub-carrier extraction module 1318 is then provided to a slopecancellation module 1320. As described above, each possible or potentialFFT window position is time shifted with respect to the reference orlocked FFT window position. To eliminate the effect of the time shift inthe calculations the slope cancellation module 1320 applies a phaseslope cancellation to the active sub-carrier frequency domainrepresentation. Any suitable method may be used to apply a phase slopecancellation to the active sub-carrier frequency domain representationsuch as, but not limited to, those described above with reference toFIGS. 7 and 9.

The slope cancelled active sub-carrier frequency domain representationgenerated by the slope cancellation module 1320 is supplied to a pilotmodulation cancellation module 1322. As described above some OFDMsystems may modulate the pilots according to a PRBS to mitigate againsthigh peaks in the time-domain envelope. For example, in DVB-T2, thepilots are BPSK modulated according to a reference sequence derived froma symbol-level PRBS and a frame-level PN-sequence. The pilot modulationcancellation module 1322 cancels or demodulates the modulation of thepilots.

The de-modulated and slope cancelled active sub-carrier frequency domainrepresentation generated by the pilot modulation cancellation module1322 is provided to a pilot extraction module 1324 configured to extractthe pilots from the de-modulated and slope cancelled active sub-carrierfrequency domain representation to generate a pilot frequency domainrepresentation. The pilots may be extracted using any suitable method,such as, but not limited, to those described above with reference toFIGS. 7 and 10.

The pilot frequency domain representation generated by the pilotextraction module 1324 is provided to a scale module 1326 configured toscale or amplify the pilot frequency domain representation to a certainlevel to maximize the dynamic range of the IFFT module 1330. Asdescribed above, the scale or amplification to be applied by the scalemodule 1326 may be determined once from the locked or reference FFTwindow position and then that scale is applied to the pilot frequencydomain representation for each other possible FFT window position.

The scaled pilot frequency domain representation generated by the scalemodule 1326 is provided to the window module 1328 which is configured toapply a window function to the scaled pilot frequency domainrepresentation. As described above, a window function applies a zerofunction to samples that fall outside a defined window. In some casesthe window function may also perform a smoothing function. Any suitablewindow function, such as, but not limited to, those described withrespect to FIG. 7, may be used.

The windowed and scaled pilot frequency domain representation generatedby the window module 1328 is provided to an IFFT module 1330 which isconfigured to generate a channel impulse response (CIR) for theparticular FFT window position being evaluated. In particular, the IFFTconverts the frequency domain representation into a time domainrepresentation. Since the frequency domain representation received bythe IFFT module 1330 represents the pilots in the frequency domain thecorresponding time domain representation provides an estimation of theCIR for the particular FFT window position.

As described above, the noise floor estimation module 1306 is configuredto estimate the noise floor for each of the channel impulse responsesgenerated by the channel impulse response generation module 1304. In theexample of FIG. 13, the noise floor estimation module 1306 comprises adecimation module 1332, a threshold module 1334 and a noise floorestimator 1336.

The decimation module 1332 is configured to receive the CIRs generatedby the channel impulse response generation module 1304 and for each CIRdecimate the CIR into a number of bins to produce a decimated CIR. Inparticular, a CIR will typically comprise thousands of samples and thedecimation reduces the number of sample to a more amendable number foranalysis. The decimation may be performed using any suitable method,such as, but limited to, those described above with reference to FIG.12. For example, in some cases decimation may comprise dividing thesamples into block of X samples and representing each block by a singlevalue which may be, for example, a sum or average.

The decimated CIR generated by the decimation module 1332 is provided toa threshold module 1334 configured to apply a threshold to the decimatedCIR to eliminate the bins or samples that are above the threshold. Asdescribed above with reference to FIG. 12 the threshold is selected toeliminate energy peaks that can be attributed to the symbol itself suchthat only the noise remains. The threshold may be selected using anysuitable method, such as, but not limited to, the methods describedabove with reference to FIG. 12.

The thresholded and decimated CIR generated by the threshold module 1334is provided to the noise floor estimator 1336 which is configured tocombine (e.g. sum or average) the bins or samples remaining after thethreshold has been applied to the decimated CIR to produce arepresentation of the noise floor of the CIR.

As described above, the optimum FFT window position selection module1308 receives the noise floor estimates generated by the noise floorestimation module 1306 and selects the potential FFT window positionwith the lowest noise floor as the optimum FFT window position forminimizing ISI. The optimum FFT window position can then be provided toa decode unit (not shown) for decoding the symbols in the OFDM signal.

Further, the decoder 1300 described in FIG. 13 may also reportadditional parametric hints to the subsequent demodulator in order toaid performance. For instance, it has been identified that the depth ofthe CIR noise floor curve—i.e. the difference between the minimum andmaximum values of the CIR noise floor curve (e.g. CIR noise floor curve1706 or CIR noise floor curve 1712 of FIG. 17)—is correlated with thewireless channel's C/N. This can be intuitively seen when consideringthe model in equation (8), which can be extended with a C/N-dependentterm W(C/N) noting the linearity of the Fourier operator. Atacquire-time, by passing the C/N parametric hint of the noise floordepth onto the demodulator, the demodulator can have a reliableindicator of the channel's C/N which enables the adaptation of certaintracking parameters (e.g. channel estimate truncation threshold) suchthat performance may be maximized when encountering, for example, highnoise conditions.

In addition to using the identified FFT window position to reduce ISI,the identified FFT window position can also be used to perform channelcentering. The term “channel centering” is used herein to describe thecorrect identification of path positions within the channel. Channelcentering ensures that the CIR can be optimally positioned, or centered,prior to the across-frequency filtering and interpolation of the pilotsfor the purposes of successful channel estimation. In a multipathchannel, particularly in the presence of low level pre-echo (e.g. lessthan 15 dB) that is not initially detected by acquire time correlationbased methods, there can be ambiguity in the true path positions of thechannel impulse response.

Reference is now made to FIGS. 14 and 15 to illustrate this ambiguityand explain the concept of channel centering. In particular, (A) of FIG.14 illustrates a main signal 1402 and a weak pre-echo 1404 that bothcomprise symbol A. This channel would have a CIR 1406. In contrast (B)of FIG. 14 illustrates the main signal 1402 and a weak post-echo 1408.This channel would have an identical CIR 1410 to the CIR 1406 in (A)because the post echo delay in (B) of FIG. 14 has extended beyond theNyquist limit of the CIR and wrapped around to appear in front of themain path. Accordingly it is not immediately evident from the analysisof the CIRs 1406 or 1410 of FIG. 15 whether the echo 1408 preceded themain signal 1402 as shown in (A) of FIG. 14 or whether the echo 1404follows the main signal 1402 as shown in (B) of FIG. 14. It is importantto identify the correct center or configuration of the channel impulseresponse to allow equalization to be effective.

The correct path positions, or center, for the CIR can be determined byapplying a plurality of different time shifts or rotations to the pilotsin the pilot-dense symbol (defined by the FFT window identified usingthe methods and systems described above) to generate possible pathpositions within the channel. A channel frequency response estimate isthen generated for each possible path position and used to equalize thepilot dense symbol. The path position (time shift/rotation)corresponding to the equalized pilot dense symbol with the lowest noiseon the L1-pre sub-carriers is then selected as the correct pathposition.

As described above in reference to FIG. 4, the P2 symbols carry L1signaling information. The L1 signaling information is split into threemain sections: the P1 signaling (which is carried in the P1 symbol) andL1-pre signaling and L1-post signaling (both carried in the P2 symbol).The L1-pre signaling enables the reception and decoding of the L1-postsignaling, which in turn conveys the parameters needed by the receiverto access the physical layer pipes. The sub-carriers which are used tocarry the L1-pre signaling information are referred to herein as theL1-pre sub-carriers. Since the L1-pre sub-carriers will be equalized bya correct channel frequency response, if an incorrect path position hasbeen used to generate the channel frequency response estimate then theL1-pre sub-carriers will not be properly equalized (i.e. noisy).Furthermore, the noise on the L1-pre sub-carriers is measured instead ofthe noise on the L1-post sub-carriers because the encoding scheme forthe L1-pre sub-carriers is known. In particular the L1-pre sub-carriersare always BPSK encoded, whereas L1-post sub-carriers may be BPSK, QPSK,16QAM or 64QAM encoded and the specific encoding scheme used for theL1-post sub-carriers is not yet known.

Reference is now made to FIG. 15 which illustrates a plurality ofdifferent time shifts of the channel impulse response 1502, 1504, 1506,1508, and 1510 which may be evaluated. If the channel was as illustratedin (B) of FIG. 14 with a weak post-echo, then the CIR 1510 would beidentified as showing the correct path positions. If, however, thechannel was as illustrated in (A) of FIG. 14 with a weak pre-echo, thenCIRs 1502, 1504, 1506 or 1508 would be identified as showing the correctpath positions. The time shift producing the least amount of noise onthe L1-pre sub-subcarriers may then be selected as the time shift to beused in decoding the OFDM signal. It will be evident to a person ofskill in the art that the examples shown in FIGS. 14 and 15 are verysimple and or only meant to illustrate the concepts. A person of skillin the art will understand that they do not reflect the bewilderingcomplexity of real-life channels that typically have many echoes.

Reference is now made to FIG. 16 which illustrates a method 1600 fordetermining the correct path positions of the channel impulse responsefor the FFT window position identified using the methods and systemsdescribed herein. The method 1600 begins at block 1602 where a frequencydomain representation of the pilots in the identified FFT windowposition is generated. This may comprise, as described above, taking theFFT of the samples of the pilot-dense symbol that fall within the windowdefined by the identified FFT window position and extracting the pilotsub-carriers. Once the pilot frequency domain representation isgenerated the method 1600 proceeds to block 1604

At block 1604, a phase rotation is applied to the pilot frequency domainrepresentation generated at block 1602. As described above withreference to FIG. 7, a time shift is represented by a phase rotation inthe frequency domain. Accordingly, applying a phase rotation implementsa time shift to the pilot time domain representation. Once the phaserotation has been applied, the method 1600 proceeds to block 1606.

At block 1606 a filter is applied to the phase rotated pilot frequencydomain representation generated at block 1604 to reduce the noise on thepilots and improve the quality of the channel estimate. In some examplesthe filter is a low pass finite impulse response (FIR) filter. Once thefilter has been applied to the phase rotated pilot frequency domainrepresentation, the method 1600 proceeds to block 1608.

At block 1608, a channel frequency response is estimated from the pilotsin the filtered and phase rotated pilot frequency domain representationgenerated at block 1606 through interpolation by, for example, polyphasefiltering. It will be evident to a person of skill in the art that thisis an example only and other interpolation methods and techniques may beused Once the channel frequency response has been generated the phaserotation applied at block 1604 is removed and the method 1600 proceedsto block 1610.

At block 1610 the channel frequency response generated in block 1608 isused to equalize the received pilot-dense symbol (e.g. P2 symbol). Insome examples, a zero forcing technique is used where the symbolsub-carriers to be equalized are divided by the channel estimate foreach sub-carrier. It will be evident to a person of skill in the artthat this is an example only and other equalization techniques andmethods may be used. Once the equalization has been performed the datasub-carriers are extracted and frequency de-interleaved. The method 1600then proceeds to block 1612.

At block 1612 the noise on the L1-pre sub-carriers is measured. TheL1-pre sub-carries are BPSK modulated so the noise on the L1-presub-carriers may be measured by evaluating the mean Euclidian distancefrom the constellation positions. For BPSK the constellation positionsare 1+0j or −1+0j.

Blocks 1604 to 1612 are repeated a plurality of times, and each time adifferent phase rotation is applied to the pilot frequency domainrepresentation. The more phase rotations are applied the higher theaccuracy of the path order (and the centering), but this comes at a highprocessing cost. Testing has shown that applying sixty-five phaserotations provides an acceptable trade-off between accuracy andprocessing cost. However it will be evident to a person of skill in theart that fewer or more phase rotations may be applied and evaluated.Once blocks 1604 to 1612 have been executed for each phase rotation, themethod 1600 proceeds to block 1614 where the rotation with the lowestnoise on the L1-pre sub-carriers is selected. The corresponding channelimpulse response will reflect the true physical channel—i.e. it willhave the correct path order and can then be correctly centered.

To be able to determine the correct path positions (and thus center theCIR) the OFDM receiver 1300 of FIG. 13 may be modified to include apositioning module (not shown) which is configured to implement, forexample, the method of FIG. 16.

Reference is now made to FIG. 17 which illustrates graphs of theresulting noise floors calculated in accordance with the methods andsystems described herein for a main signal with a pre-echo outside theguard interval and a main signal with a post-echo outside the guardinterval. In particular (A) of FIG. 17 illustrates a main signal 1702with a pre-echo 1704 that is outside the guard interval. This results inthe CIR noise floor curve 1706 as a function of FFT window position. Itcan be seen that the lowest noise floor is achieved when the FFT windowis positioned at the starting edge of the guard interval indicating thisis the best or optimum position for the FFT window to minimize totalISI. Specifically, when the FFT window is positioned here it is able togain the most power from the echo 1704 while still being able toproperly decode symbol A from the main signal 1702.

In contrast, (B) of FIG. 17 illustrates a main signal 1708 and apost-echo 1710 that is outside the guard interval. This results in theCIR noise floor curve 1712. It can be seen that in this case the lowestnoise floor is achieved when the FFT window is positioned at the endedge of the guard interval indicating this is the best or optimumposition for the FFT window position to minimize total ISI.

Since the methods and systems described here rely solely on theinformation in a single pilot-dense symbol (e.g. P2 symbol), the methodcan be performed once to determine the optimum FFT window position fordecoding the symbols of the OFDM signal. Ideally the analysis isperformed at the beginning of receiver operation because there is adelay before the OFDM signal can be demodulated where the OFDM receiveris obtaining the parameters for decode. In particular, the first frameis used obtain the parameters for decoding so the OFDM receiver can'tstart decoding frames just by looking at one frame. This provides idletime for the position of the FFT window to be identified using themethods described above. This is in contrast with many other systems forreducing ISI which require continual monitoring.

By doing such a comprehensive analysis once, at the beginning ofreceiver operation, the OFDM receiver can more quickly converge to thebest quality bit error rate. This means that users don't have to put upwith excessive errors at the beginning of receiver operation.

That said, the methods described herein could be reconfigured such thatinstead of selecting and evaluating a high number of potential orpossible FFT window positions, only a few possible or potential windowpositions are selected and evaluated frequently (e.g. per frame) in, forexample, an early-later tracking fashion. This of course has thedisadvantage of taking much more time to converge and being much morecomputationally intensive. One of the advantages, however, is the addedability to explicitly measure total ISI in dynamically changing channelsif so desired. With a combination of acquire-time analysis andearly-late tracking for dynamic, explicit ISI minimization is alsopossible using the pilot-aided, noise-floor based method disclosedherein.

The term ‘processor’ and ‘computer’ are used herein to refer to anydevice, or portion thereof, with processing capability such that it canexecute instructions. The term ‘processor’ may, for example, includecentral processing units (CPUs), graphics processing units (GPUs orVPUs), physics processing units (PPUs), radio processing units (RPUs),digital signal processors (DSPs), general purpose processors (e.g. ageneral purpose GPU), microprocessors, any processing unit which isdesigned to accelerate tasks outside of a CPU, etc. Those skilled in theart will realize that such processing capabilities are incorporated intomany different devices and therefore the term ‘computer’ includes settop boxes, media players, digital radios, PCs, servers, mobiletelephones, personal digital assistants and many other devices.

Those skilled in the art will realize that storage devices utilized tostore program instructions can be distributed across a network. Forexample, a remote computer may store an example of the process describedas software. A local or terminal computer may access the remote computerand download a part or all of the software to run the program.Alternatively, the local computer may download pieces of the software asneeded, or execute some software instructions at the local terminal andsome at the remote computer (or computer network). Those skilled in theart will also realize that by utilizing conventional techniques known tothose skilled in the art that all, or a portion of the softwareinstructions may be carried out by a dedicated circuit, such as a DSP,programmable logic array, or the like.

Memories storing machine executable data for use in implementingdisclosed aspects can be non-transitory media. Non-transitory media canbe volatile or non-volatile. Examples of volatile non-transitory mediainclude semiconductor-based memory, such as SRAM or DRAM. Examples oftechnologies that can be used to implement non-volatile memory includeoptical and magnetic memory technologies, flash memory, phase changememory, resistive RAM.

A particular reference to “logic” refers to structure that performs afunction or functions. An example of logic includes circuitry that isarranged to perform those function(s). For example, such circuitry mayinclude transistors and/or other hardware elements available in amanufacturing process. Such transistors and/or other elements may beused to form circuitry or structures that implement and/or containmemory, such as registers, flip flops, or latches, logical operators,such as Boolean operations, mathematical operators, such as adders,multipliers, or shifters, and interconnect, by way of example. Suchelements may be provided as custom circuits or standard cell libraries,macros, or at other levels of abstraction. Such elements may beinterconnected in a specific arrangement. Logic may include circuitrythat is fixed function and circuitry can be programmed to perform afunction or functions; such programming may be provided from a firmwareor software update or control mechanism. Logic identified to perform onefunction may also include logic that implements a constituent functionor sub-process. In an example, hardware logic has circuitry thatimplements a fixed function operation, or operations, state machine orprocess.

Any range or device value given herein may be extended or alteredwithout losing the effect sought, as will be apparent to the skilledperson.

It will be understood that the benefits and advantages described abovemay relate to one embodiment or may relate to several embodiments. Theembodiments are not limited to those that solve any or all of the statedproblems or those that have any or all of the stated benefits andadvantages.

Any reference to ‘an’ item refers to one or more of those items. Theterm ‘comprising’ is used herein to mean including the method blocks orelements identified, but that such blocks or elements do not comprise anexclusive list and an apparatus may contain additional blocks orelements and a method may contain additional operations or elements.Furthermore, the blocks, elements and operations are themselves notimpliedly closed.

The steps of the methods described herein may be carried out in anysuitable order, or simultaneously where appropriate. The arrows betweenboxes in the figures show one example sequence of method steps but arenot intended to exclude other sequences or the performance of multiplesteps in parallel. Additionally, individual blocks may be deleted fromany of the methods without departing from the spirit and scope of thesubject matter described herein. Aspects of any of the examplesdescribed above may be combined with aspects of any of the otherexamples described to form further examples without losing the effectsought. Where elements of the figures are shown connected by arrows, itwill be appreciated that these arrows show just one example flow ofcommunications (including data and control messages) between elements.The flow between elements may be in either direction or in bothdirections.

It will be understood that the above description of a preferredembodiment is given by way of example only and that variousmodifications may be made by those skilled in the art. Although variousembodiments have been described above with a certain degree ofparticularity, or with reference to one or more individual embodiments,those skilled in the art could make numerous alterations to thedisclosed embodiments without departing from the spirit or scope of thisinvention.

What is claimed is:
 1. A method of determining correct path positions ofa channel impulse response for a particular FFT window position at anorthogonal frequency-division multiplexing receiver, the methodcomprising: generating a frequency domain representation of pilots in areceived pilot-dense symbol of an orthogonal frequency-divisionmultiplexing signal based on the particular FFT window position;applying each of a plurality of phase rotations to the frequency domainrepresentation of the pilots to generate a plurality of phase rotatedfrequency domain representations of the pilots; generating a channelfrequency response estimate for each phase rotated frequency domainrepresentation of the pilots; equalizing the received pilot-dense symbolbased on each channel frequency response estimate; measuring an amountof noise on L1-pre sub-carriers for each equalized pilot-dense symbol;and selecting path positions based on the phase rotation associated withthe channel frequency response producing the lowest noise on the L1-presub-carriers as the correct path positions.
 2. The method of claim 1,wherein generating the frequency domain representation of the pilotscomprises: performing a FFT on samples of the received pilot-densesymbol falling within an FFT window defined by the particular FFT windowposition to generate a frequency domain representation of thepilot-dense symbol; and extracting pilot sub-carriers from the frequencydomain representation of the pilot-dense symbol to generate thefrequency domain representation of the pilots.
 3. The method of claim 1,further comprising, prior to generating the channel frequency responseestimate for each phase rotated frequency domain representation of thepilots, applying a filter to the phase rotated frequency domainrepresentation of the pilots.
 4. The method of claim 3, wherein thefilter is a low pass finite impulse response filter.
 5. The method ofclaim 1, wherein the channel frequency response estimate for each phaserotated frequency domain representation of the pilots is generatedthrough interpolation by polyphase filtering.
 6. The method of claim 1,wherein the L1-pre sub-carriers are BPSK modulated, and measuring theamount of noise on the L1-pre sub-carriers for each equalizedpilot-dense symbol comprises evaluating a mean Euclidian distance fromconstellation positions.
 7. The method of claim 1, further comprisingdecoding one or more symbols of the orthogonal frequency-divisionmultiplexing signal based on the correct path positions.
 8. The methodof claim 1, wherein the particular FFT window was selected by:estimating a channel impulse response from the received pilot-densesymbol for each of a plurality of potential FFT window positions;determining a noise floor of each of the channel impulse responses; andselecting the potential FFT window position corresponding to the channelimpulse response with the lowest noise floor as the particular FFTwindow position.
 9. An orthogonal frequency-division multiplexingreceiver comprising a positioning module configured to: generate afrequency domain representation of pilots in a received pilot-densesymbol of an orthogonal frequency-division multiplexing signal based ona particular FFT window position; apply each of a plurality of phaserotations to the frequency domain representation of the pilots togenerate a plurality of phase rotated frequency domain representationsof the pilots; generate a channel frequency response estimate for eachphase rotated frequency domain representation of the pilots; equalizethe received pilot-dense symbol based on each channel frequency responseestimate; measure an amount of noise on L1-pre sub-carriers for eachequalized pilot-dense symbol; and select path positions based on thephase rotation associated with the channel frequency response producingthe lowest noise on the L1-pre sub-carriers as the correct pathpositions.
 10. The orthogonal frequency-division multiplexing receiverof claim 9, wherein the positioning module is configured to generate thefrequency domain representation of the pilots by: performing a FFT onsamples of the received pilot-dense symbol falling within an FFT windowdefined by the particular FFT window position to generate a frequencydomain representation of the pilot-dense symbol; and extracting pilotsub-carriers from the frequency domain representation of the pilot-densesymbol to generate the frequency domain representation of the pilots.11. The orthogonal frequency-division multiplexing receiver of claim 9,wherein the positioning module is further configured to, prior togenerating the channel frequency response estimate for each phaserotated frequency domain representation of the pilots, apply a filter tothe phase rotated frequency domain representations of the pilots. 12.The orthogonal frequency-division multiplexing receiver of claim 11,wherein the filter is a low pass finite impulse response filter.
 13. Theorthogonal frequency-division multiplexing receiver of claim 9, whereinthe positioning module is configured to generate the channel frequencyresponse estimate for each phase rotated frequency domain representationof the pilots through interpolation by polyphase filtering.
 14. Theorthogonal frequency-division multiplexing receiver of claim 9, whereinthe L1-pre sub-carriers are BPSK modulated, and the positioning moduleis configured to measure the amount of noise on the L1-pre sub-carriersfor each equalized pilot-dense symbol by evaluating a mean Euclidiandistance from constellation positions.
 15. The orthogonalfrequency-division multiplexing receiver of claim 9, further comprisinga decode unit configured to decode one or more symbols of the orthogonalfrequency-division multiplexing signal based on the correct pathpositions.
 16. The orthogonal frequency-division multiplexing receiverof claim 9, wherein the particular FFT window is selected by: estimatinga channel impulse response from the received pilot-dense symbol for eachof a plurality of potential FFT window positions; determining a noisefloor of each of the channel impulse responses; and selecting thepotential FFT window position corresponding to the channel impulseresponse with the lowest noise floor as the particular FFT windowposition.
 17. The orthogonal frequency-division multiplexing receiver ofclaim 9, wherein the orthogonal frequency-division multiplexing receiveris embodied in hardware.
 18. A non-transitory computer readable storagemedium having stored thereon computer readable code configured to causeat least one processor to perform the method of claim 1 when the code isrun.